https://github.com/johnwlambert/argoverse-centerpoint-simplified
Inference with pre-trained CenterPoint models on the Argoverse dataset
https://github.com/johnwlambert/argoverse-centerpoint-simplified
Last synced: about 1 year ago
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Inference with pre-trained CenterPoint models on the Argoverse dataset
- Host: GitHub
- URL: https://github.com/johnwlambert/argoverse-centerpoint-simplified
- Owner: johnwlambert
- Created: 2020-12-10T16:45:09.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2021-01-16T00:58:41.000Z (over 5 years ago)
- Last Synced: 2025-05-15T22:18:43.381Z (about 1 year ago)
- Language: Python
- Homepage:
- Size: 231 KB
- Stars: 12
- Watchers: 3
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# CenterPoint for Argoverse Data
This repository is a simplified version of the [original CenterPoint repo](https://github.com/tianweiy/CenterPoint), with far less code, designed purely for inference (not for training).
## Installation
Environment:
- Python 3.8.3
**Dependencies**
- SparseConv (build locally)
- DCN (build locally), produce deform_conv_cuda.cpython-38-x86_64-linux-gnu.so
- Iou3dNMS (build locally), produce iou3d_nms_cuda.cpython-38-x86_64-linux-gnu.so
- Pytorch 1.7.1 (check with `python -c "import torch; print(torch.__version__)"`)
- argoverse-api
- CUDA 11.0 (check with `python -c "import torch; print(torch.version.cuda)"`)
If you wish to run `viz_aggregated_sweeps.py`, you must run:
Mayavi Environment: https://github.com/mne-tools/mne-python/blob/master/environment.yml
## Bug Fixed addressed
https://github.com/pytorch/pytorch/issues/29642
use torch::RegisterOperators
Not a problem if you use latest Pytorch?
nvcc fatal : Unknown option '-Wall'
https://github.com/traveller59/spconv/issues/69
CUDACXX=/usr/local/cuda/bin/nvcc python setup.py bdist_wheel
pip install * --force-reinstall
https://pytorch.org/get-started/previous-versions/
- RuntimeError: /nethome/jlambert30/spconv/src/spconv/indice.cu 274
cuda execution failed with error 98 invalid device function
prepareSubMGridKernel failed
https://github.com/traveller59/spconv/issues/34
Make sure you use the same CUDA version for all installations (set CUDA_HOME before building anything)
## Deformable Convolution
Added here:
https://github.com/pytorch/vision/pull/1586/files
## nuScenes Coordinate System
The nuScenes egovehicle coordinate frame is situated on the ground underneath the center of rear axle. Consider the pose of the LiDAR sensor in the egovehicle frame:
```python
egovehicle_SE3_lidar.translation
array([0.94, 0. , 1.84 ])
```
This means the LiDAR is on the center of the car, 1.84 meters above the ground. It is also almost one meter forward (+x) from the rear axle.
What about the relative orientation between the frames?
```python
Rotation.from_matrix(egovehicle_SE3_lidar.rotation).as_euler('zyx', degrees=True)
array([-89.9, 1.4, 0.3])
```
We see that the LiDAR frame is basically rotated -90 degrees from the egovehicle frame
```python
np.round(egovehicle_SE3_lidar.transform_point_cloud(np.eye(3)),2)
array([[ 0.95, -1. , 1.83],
[ 1.94, 0. , 1.82],
[ 0.97, -0.01, 2.84]])
```
## Another Option for DCN:
Pytorch deformable conv: https://pytorch.org/docs/stable/_modules/torchvision/ops/deform_conv.html#deform_conv2d